The VC dimension and Rademacher complexity are widely used to analyze the expressive capacity and generalization of classical parametric machine learning models [1]}, [2]}, [3]}, [4]}, [5]}. A series of works investigate the VC dimension and Rademacher complexity of deep learning models.
